A CLI tool that scores arXiv papers for genuine novelty against your personal reading history, so researchers stop re-reading recycled ideas

Customer: Solo ML researcher or technical lead at a seed-stage AI startup — reads 15-25 papers/week on arXiv, tracks papers in Notion or Zotero, constantly annoyed that 40% of papers are incremental tweaks on things they already know cold

Problem: No tool compares a new paper against your specific reading history before you invest 45 minutes reading it — generic recommenders optimize for popularity or citation count, not personal knowledge gaps

Pricing: one-time — $800 in first 60 days via lifetime licenses, then reassess

Why now

Claude Haiku and cheap vector DBs (sqlite-vec, ChromaDB) make per-paper semantic scoring cost under $0.001 — the unit economics now support a lightweight personal tool where 12 months ago it was cost-prohibitive; arXiv volume also hit record highs in 2025, making the signal-to-noise problem acute

Go-to-market

1. Post a ‘Show HN’ with a demo GIF showing a paper getting flagged as 90% novel vs. one getting scored 15% novel with an explanation — HN ML researchers are the exact persona and will give brutally honest feedback
2. Drop the open-source repo on GitHub with a MIT license, but sell a $29 lifetime ‘Supporter Edition’ that adds a weekly digest email and a Zotero sync plugin — keep the core free to drive organic spread
3. Post a short Twitter/X thread tagging 3-5 ML researchers known for sharing paper summaries (e.g., Andrej Karpathy-style accounts) showing your own novelty scores on last week’s hot papers — invites public engagement
4. DM 10 ML PhD students on Reddit r/MachineLearning offering a free beta key in exchange for a 15-min feedback call — they read the most papers and will surface edge cases fast

Moat (or lack thereof)

No real moat — the core idea is simple enough that Semantic Scholar, Elicit, or a well-funded competitor could add this as a feature in a sprint. The defensibility is purely personal data flywheel: the longer someone uses it, the more calibrated their personal corpus becomes, making switching mildly annoying. That’s habit-stickiness, not a moat. Ship fast, charge a one-time fee, and don’t pretend otherwise.